基于MF-DCCA 的呼吸道疾病与大气污染物相关性分析

大气与环境光学学报 ›› 2021, Vol. 16 ›› Issue (1): 35-43.

基于MF-DCCA 的呼吸道疾病与大气污染物相关性分析

黄毅1;2, 郑凯莉3, 彭立平2, 刘春琼4, 杨艺池2

1 江西财经大学统计学院, 江西南昌 330013; 2 吉首大学数学与统计学院, 湖南吉首 416000; 3 吉首大学旅游与管理工程学院, 湖南张家界 427000; 4 吉首大学生物资源与环境科学学院, 湖南吉首 416000

收稿日期:2019-11-13 修回日期:2020-05-13 出版日期:2021-01-28 发布日期:2021-02-02
通讯作者: E-mail: huangy0014@163.com E-mail:huangy0014@163.com
作者简介:黄毅 (1990 - ), 湖南张家界人, 博士研究生, 讲师, 主要研究方向为大气污染物的复杂性。 E-mail: huangy0014@163.com
基金资助:
Supported by National Natural Science Foundation (国家自然科学基金, 41603128), Project of the Natural Science Fund of Hunan Province (湖南省自然科学基金, 2017JJ2219), Project of Hunan Education Department (湖南省教育厅项目, 19C1515), Open Fund for key Laboratories of Ecotourism in Hunan Province (生态旅游湖南省重点实验室开放基金, STLV1812), Scientific Research Project of Jishou University (吉首大学校级科研项目, Jdy1804)

Multifractal Detrended Cross-Correlation Analysis of Incidence Rate of Respiratory Diseases and Atmospheric Pollutants

HUANG Yi 1;2, ZHENG Kaili 3, PENG Liping2, LIU Chunqiong4, YANG Yichi2

1 School of Statistics, Jiangxi University of Finance and Economics, Nanchang 330013 China; 2 Department of Mathematic and Statistics, Jishou University, Jishou 416000, China; 3 Department of Tourisim and Administrative Engineering, Jishou University, Zhangjiajie 427000, China; 4 Department of Biology and Environmental Sciences, Jishou University, Jishou 416000, China

Received:2019-11-13 Revised:2020-05-13 Published:2021-01-28 Online:2021-02-02

摘要/Abstract

摘要： 针对呼吸道系统疾病与大气 PM2:5、 SO2 浓度序列的相关性特征, 应用多重分形消除趋势波动分析法 (MF-DCCA), 对张家界市永定区呼吸道系统疾病患病人数与大气 PM2:5、 SO2 浓度序列进行了研究。结果发现该地区呼吸道系统疾病患病人数与大气 PM2:5、 SO2 浓度的相关性具有长期持续特征和多重分形特征。随后对它们相关性多重分形特征的动力来源进行了分析, 通过随机重排和相位随机处理, 结果表明在不同时间尺度上的长期持续性影响是其主要动力来源。进一步研究发现该地区呼吸道系统疾病与大气 PM2:5、 SO2 浓度序列的相关性在四个季节均具有长期持续性的多重分形特征, 且夏季多重分形特征相对强于其他季节。

关键词: PM2:5, SO2, 多重分形, 呼吸道系统疾病, 大气污染物

Abstract: In order to get a better understanding of the correlation between respiratory diseases outpatients and atmospheric PM2:5, SO2 concentrations, multifractal detrended cross-correlation analysis (MF-DCCA) was used to study the sequence of respiratory diseases outpatients and PM2:5, SO2 concentrations in Yongding District. The results show that the correlation between respiratory diseases outpatients and atmospheric PM2:5, SO2 concentrations has the characteristics of long-term persistence and multifractal. Then the dynamic sources of their correlation multifractal features are analyzed. Through random rearrangement and phase randomization procedure, the results show that the long-term persistence effect is the main driving force at different time scales. Further study found that the correlation between respiratory system diseases and atmospheric PM2:5, SO2 concentrations sequence in the four seasons has long-term multifractal characteristics, and the multiple fractal features in summer are stronger than those in other seasons.

Key words: PM2:5, SO2, multifractal, respiratory diseases, atmospheric pollutant

中图分类号:

R122

黄毅, 郑凯莉, 彭立平, 刘春琼, 杨艺池. 基于MF-DCCA 的呼吸道疾病与大气污染物相关性分析[J]. 大气与环境光学学报, 2021, 16(1): 35-43.

HUANG Yi , ZHENG Kaili , PENG Liping, LIU Chunqiong, YANG Yichi. Multifractal Detrended Cross-Correlation Analysis of Incidence Rate of Respiratory Diseases and Atmospheric Pollutants[J]. Journal of Atmospheric and Environmental Optics, 2021, 16(1): 35-43.

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